An image feature extraction device configured to extract an image feature representing the feature of an image is used, for example, to search for the similarity between images or moving images, which are collections of images. That is to say, the image feature extraction device compares the image features extracted from the respective images with each other to calculate an image similarity representing the degree of similarity between the images, and determines the similarity between the images.
A method for extracting an image feature for the purpose of searching for the similarity between images is described in, for example, Patent Documents 1 and 2. In the method described in these documents, an image feature appropriate for search for the similarity between images is extracted.
On the other hand, there is an image feature extraction device configured to extract an image feature for the purpose of detecting a copy of an image or a moving image, which is a collection of images. In this case, the image feature extraction device compares the image features extracted from the respective images with each other to calculate an identity scale representing the degree of identity of images, and compares the calculated identity scale with a certain threshold value to determine whether or not the images are identical (whether one of the images is a copy of the other).
When an image is copied, various alteration processes are usually executed. Various alteration processes include conversion of the compression format of an image, conversion of the compression ratio of an image, conversion of the size/aspect ratio of an image, adjustment of the color tone of an image, various filtering processes on an image (sharpening, smoothing), and so on. Moreover, various alteration processes include local processing on an image such as superimposition of a caption, and so on. Hereinafter, not only simply copying an image but also copying with execution of various alteration processes as mentioned above will be simply referred to as copying. Moreover, hereinafter, various alteration processes shall mean various alteration processes on an image as described above. Accordingly, in order to detect a copy of an image, an image feature extraction device is required to extract an image feature in a robust manner against various alteration processes (without being influenced by various alteration processes). Moreover, an image feature extraction device is required to extract image features that make it possible to calculate an identity scale allowing determination that an image copied by various alteration processes is an image identical to an original image when comparing image features.
A method for extracting an image feature robustly against various alteration processes for the purpose of detecting a copy of an image is described in Non-Patent Documents 1 to 3. In the method described in these documents, firstly, a feature is extracted from each of a plurality of local regions of an image, the extracted feature is quantized to calculate a quantization index, and the quantization index of each of the local regions is extracted as an image feature. When two images are compared, quantization indexes of corresponding local regions are compared, and an identity scale is calculated based on the number of local regions whose quantization indexes coincide.
In Non-Patent Document 1, the patterns of luminance distribution within local regions are classified into eleven types, which are referred to as quantization indexes.
Further, in Non-Patent Document 2, color information of a local region is normalized by a time interval and then subjected to linear scalar quantization, the result of which is referred to as a quantization index. An identity scale is calculated as a Hamming distance.
Furthermore, in Non-Patent Document 3 (a technique described as “Local Edge Representation” of Non-Patent Document 3), the position of the center of gravity of edge points extracted from a local region is quantized, which is regarded as a quantization index.
FIG. 1 is a block diagram showing a configuration of an image feature extraction device described in Non-Patent Documents 1 to 3. With reference to FIG. 1, the image feature extraction device described in Non-Patent Documents 1 to 3 is composed of an image feature extraction device 11.
With reference to FIG. 1, the image feature extraction device 11 is composed of a feature extraction unit 111 and a quantization index calculation unit 112. When an image is inputted, the feature extraction unit 111 extracts a feature for each of a plurality of previously defined local regions, and supplies the extracted feature of each of the local regions to the quantization index calculation unit 112. The quantization index calculation unit 112 quantizes the feature of each of the local regions supplied by the feature extraction unit 111 to calculate a quantization index, and outputs the quantization index of each of the local regions as a feature of the image.
Further, FIG. 2 is a block diagram showing a configuration of an image feature comparison device 12 configured to compare image features extracted by the image feature extraction device described in Non-Patent Documents 1 to 3 and calculate an identity scale representing the degree of identity of images. With reference to FIG. 2, the image feature comparison device 12 is composed of a quantization index comparison unit 121. The quantization index comparison unit 121 is supplied as inputs with quantization indexes of respective local regions of two images outputted by the image feature extraction devices 11, compares the quantization indexes for each corresponding local region, calculates an identity scale based on the number of local regions whose quantization indexes coincide, and outputs the identity scale.
The image feature extraction device with the configuration shown in FIG. 1 uses, as a feature, a quantization index calculated by quantizing a feature, and therefore, has robustness against some change of image signals resulting from various alteration processes on an image. Moreover, the image feature extraction device is capable of using a quantization index of each of local regions as a feature and calculating an identity scale based on the number of local regions whose quantization indexes coincide, and therefore, also has robustness against an alteration process like local processing on an image, such as superimposition of a caption.
[Patent Document 1] Japanese Unexamined Patent Application Publication No. 2000-259832 “Image Feature Amount Generator, Image Retrieval Device, and Generation Method and Retrieval Method Therefor”
[Patent Document 2] Japanese Unexamined Patent Application Publication No. 2001-167118 “Device and Method for Retrieving Picture, and Storage Medium with Similar Picture Retrieving Program Recorded Thereon”
[Non-Patent document 1] Kota Iwamoto, Eiji Kasutani, Akio Yamada, “Image signature Robust to Caption Superimposition for Video Sequence Identification,” Proceedings of International Conference on Image processing (ICIP2006), 2006
[Non-Patent document 2] Takayuki Kurozumi, Hidehisa Nagano, Kunio Kasino, “Robust Video Search Method for Video Signal Queries Captured in the Real World,” IEICE (the Institute Of Electronics, Information and Communication Engineers) Transactions Vol. J90-D No. 8, pp. 2223-2231, August 2007
[Non-Patent document 3] Arun Hampapur, Ruud M. Bolle, “Comparison of Distance Measures for Video Copy Detection,” Proceedings of International Conference on Multimedia and Expo (ICME2001), p. 946, 2001
However, since the image feature extraction device with the configuration shown in FIG. 1 extracts one quantization index set quantized by one quantization method having been previously defined as an image feature, there is a problem that, in a case that extracted image features are compared and the identity of images is determined, the capability of determining identity of images is fixed by a quantization method to be used. Here, the capability of determining identity of images depends on two scales: identification capability, which is the degree of capability of identifying different images; and robustness, which is the degree of resistance of a quantization index to various alteration processes on an image. Identification capability and robustness have a trade-off relation. Fixation of the capability of determining identity of images also refers to fixation of the balance of identification capability and robustness.